microorganisms

Article Infection among Ixodid Exhibits Species Dependence and Suggests a Vertical Pattern of Transmission

Shohei Ogata 1, Wessam Mohamed Ahmed Mohamed 1 , Kodai Kusakisako 1,2, May June Thu 1,†, Yongjin Qiu 3 , Mohamed Abdallah Mohamed Moustafa 1,4 , Keita Matsuno 5,6 , Ken Katakura 1, Nariaki Nonaka 1 and Ryo Nakao 1,*

1 Laboratory of Parasitology, Department of Disease Control, Faculty of Veterinary Medicine, Graduate School of Infectious Diseases, Hokkaido University, N 18 W 9, Kita-ku, Sapporo 060-0818, Japan; [email protected] (S.O.); [email protected] (W.M.A.M.); [email protected] (K.K.); [email protected] (M.J.T.); [email protected] (M.A.M.M.); [email protected] (K.K.); [email protected] (N.N.) 2 Laboratory of Veterinary Parasitology, School of Veterinary Medicine, Kitasato University, Towada, Aomori 034-8628, Japan 3 Hokudai Center for Zoonosis Control in Zambia, School of Veterinary Medicine, The University of Zambia, P.O. Box 32379, Lusaka 10101, Zambia; [email protected] 4 Department of Medicine, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt 5 Unit of Risk Analysis and Management, Research Center for Zoonosis Control, Hokkaido University, N 20 W 10, Kita-ku, Sapporo 001-0020, Japan; [email protected]  6 International Collaboration Unit, Research Center for Zoonosis Control, Hokkaido University, N 20 W 10,  Kita-ku, Sapporo 001-0020, Japan Citation: Ogata, S.; Mohamed, * Correspondence: [email protected]; Tel.: +81-11-706-5196 W.M.A.; Kusakisako, K.; Thu, M.J.; † Present address: Food Control Section, Department of Food and Drug Administration, Ministry of Health and Sports, Zabu Thiri, Nay Pyi Taw 15011, Myanmar. Qiu, Y.; Moustafa, M.A.M.; Matsuno, K.; Katakura, K.; Nonaka, N.; Nakao, R. Spiroplasma Infection among Ixodid Abstract: Members of the genus Spiroplasma are Gram-positive without cell walls. Some Ticks Exhibits Species Dependence Spiroplasma species can cause disease in such as , whereas others provide their host and Suggests a Vertical Pattern of with resistance to pathogens. Ticks also harbour Spiroplasma, but their role has not been elucidated yet. Transmission. Microorganisms 2021, 9, Here, the infection status and genetic diversity of Spiroplasma in ticks were investigated using samples 333. https://doi.org/10.3390/ collected from different geographic regions in Japan. A total of 712 ticks were tested for Spiroplasma microorganisms9020333 infection by PCR targeting 16S rDNA, and Spiroplasma species were genetically characterized based on 16S rDNA, ITS, dnaA, and rpoB gene sequences. A total of 109 samples originating from eight Academic Editors: David S. Lindsay species were positive for Spiroplasma infection, with infection rates ranging from 0% to 84% and Vittorio Sambri depending on the species. A linear mixed model indicated that tick species was the primary factor Received: 24 December 2020 associated with Spiroplasma infection. Moreover, certain Spiroplasma alleles that are highly adapted to Accepted: 5 February 2021 specific tick species may explain the high infection rates in ovatus and Haemaphysalis kitaokai. Published: 8 February 2021 A comparison of the alleles obtained suggests that horizontal transmission between tick species

Publisher’s Note: MDPI stays neutral may not be a frequent event. These findings provide clues to understand the transmission cycle of with regard to jurisdictional claims in Spiroplasma species in wild tick populations and their roles in host ticks. published maps and institutional affil- iations. Keywords: Haemaphysalis; Ixodes; Spiroplasma; symbionts; ticks; Japan

1. Introduction Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Members of the genus Spiroplasma are Gram-positive bacteria without cell walls. They This article is an open access article are known as symbionts of arthropods and plants and are classified into three major distributed under the terms and based on the 16S ribosomal RNA gene (rDNA) sequence: Ixodetis, Citri-Chrysopicola- conditions of the Creative Commons Mirum (CCM), and Apis [1,2]. Spiroplasma is one of the most common endosymbionts Attribution (CC BY) license (https:// with a wide range of hosts, including insects, , crustaceans, and plants [3]. It is creativecommons.org/licenses/by/ estimated that 5–10% of insect species harbor this symbiont group [2,4]. 4.0/).

Microorganisms 2021, 9, 333. https://doi.org/10.3390/microorganisms9020333 https://www.mdpi.com/journal/microorganisms Microorganisms 2021, 9, 333 2 of 17

Spiroplasma has a wide range of fitness effects and transmission strategies [2,5–17]. Some Spiroplasma species affect the sex ratio by inducing male killing in hosts such as flies, butterflies, and ladybird [7–10]. Several Spiroplasma species are known to cause disease in arthropods such as bees and plants [6,17,18]. On the other hand, some flies infected with Spiroplasma can develop resistance to other pathogens [5,10–12]. A wide range of symbiotic relationships involving Spiroplasma have been observed [5,7,8,14–16]. The rapid spread of Spiroplasma infection in fruit fly natural populations has been reported in some areas of North America, and this phenomenon has been confirmed in laboratory settings [19]. This characteristic of Spiroplasma is not only biologically interesting, but also useful for symbiotic control applications among host individuals [20]. Ticks have long been studied, since they transmit a variety of pathogens to humans and . is the first reported tick-associated Spiroplasma, which was obtained from Haemaphysalis leporispalustris in the United States in 1982 during the search for rickettsiae in ticks [21]. Another species, S. ixodetis, was isolated from Ixodes pacificus in the United States in 1981 [22]. Thus far, these two species are the only validated Spiroplasma species detected in ticks. Nevertheless, several alleles or putative new species of Spiroplasma have been found in various tick species such as I. arboricola, I. frontalis, I. ovatus, I. persulcatus, I. ricinus, I. uriae, Dermacentor marginatus, Rhipicephalus annulatus, R. decoloratus, R. geigyi, and R. pusillus [23–30]. In Japan, 46 tick species belonging to seven genera (Amblyomma, Argas, Dermacentor, Rhipicephalus, Haemaphysalis, Ixodes, and Ornithodoros) have been recorded [11,12]. Several tick-borne diseases such as , relapsing fever, Japanese spotted fever, severe fever with thrombocytopenia syndrome, and tick-borne encephalitis are endemic [31]. Taroura et al. first detected Spiroplasma DNA in questing I. ovatus ticks captured in several prefectures [24]. Subsequently, a microbiome study revealed the presence of Spiroplasma in the salivary glands of I. ovatus and I. persulcatus [23]. More recently, several Spiroplasma isolates were obtained by incubating the homogenates of I. monospinosus, I. persulcatus, and H. kitaokai with tick and mosquito cells [32]. These studies collectively indicate that there is a close relationship between Spiroplasma and ticks in Japan; however, no comprehensive studies have been conducted to determine the genetic diversity and prevalence of tick- associated Spiroplasma. The aim of this study was to identify and genetically characterize Spiroplasma in different tick species in Japan. A linear mixed model (LMM) was developed to resolve the correlation among several extrinsic and intrinsic factors associated with Spiroplasma infection in ticks.

2. Materials and Methods 2.1. Sample Collection Ticks were collected by flagging the vegetation during the period of tick activity (between April 2013 and August 2018) at 112 different sampling sites in 19 different prefectures in Japan. The sampling sites were classified into nine geographical blocks: Hokkaido (Hokkaido prefecture), Tohoku (Yamagata and Fukushima prefectures), Kanto (Chiba prefecture), Chubu (Nagano and Shizuoka prefectures), Kinki (Mie, Nara, and Wakayama prefectures), Chugoku (Hiroshima and Shimane prefectures), Shikoku (Kagawa, Ehime, and Kochi prefectures), Kyushu (Nagasaki, Kumamoto, Miyazaki, and Kagoshima prefectures), and Okinawa (Okinawa prefecture). All collected ticks were transferred to Petri dishes and preserved in an incubator at 16 ◦C until use.

2.2. Identification of Tick Species Tick species were identified morphologically under a stereomicroscope according to standard morphological keys [33,34]. A total of 712 adult ticks from four genera were examined in this study. These included two species in the genus Amblyomma (A. geoemydae, n = 3; A. testudinarium, n = 26), one species in the genus Dermacentor (D. taiwanensis, n = 9), 10 species in the genus Haemaphysalis (H. concinna, n = 2; H. cornigera, n = 1; H. flava, n = 65; Microorganisms 2021, 9, 333 3 of 17

H. formosensis, n = 83; H. hystricis, n = 60; H. japonica, n = 20; H. kitaokai, n = 78; H. longicornis, n = 106; H. megaspinosa, n = 66; H. yeni, n = 1), and seven species in the genus Ixodes (I. monospinosus, n = 21; I. nipponensis, n = 3; I. ovatus, n = 80; I. pavlovsky, n = 26; I. persulcatus, n = 55; I. tanuki, n = 1; I. turdus, n = 6).

2.3. DNA Extraction The procedures for DNA extraction from individual ticks have been reported previ- ously [35]. In brief, the surface of tick bodies was individually washed with 70% ethanol and sterilized phosphate-buffered solution (PBS). The whole tick bodies were homogenized in 100 µL of high-glucose Dulbecco’s modified Eagle’s medium (Gibco, Life Technologies, Grand Island, NY, USA) using Micro Smash MS100R (TOMY, Tokyo, Japan) for 30 s at 3000 rpm. DNA was extracted from 50 µL of the tick homogenate using the blackPREP Tick DNA/RNA Kit (Analytik Jena, Jena, Germany) according to the manufacturer’s protocol.

2.4. Detection of Spiroplasma in Ticks To detect Spiroplasma DNA, PCR amplification of a sequence of approximately 1028 bp in the 16S rDNA was performed. The PCR was carried out in a 20 µL reaction mixture containing 10 µL of 2× Gflex PCR Buffer (Mg2+, dNTP plus), 400 nM of Tks Gflex™ DNA Polymerase (Takara Bio, Shiga, Japan), 400 nM of each primer, 1 µL of DNA template, and sterilized water. The reaction was performed at 94 ◦C for 1 min, followed by 45 cycles at 98 ◦C for 10 s, 60 ◦C for 30 s, and 68 ◦C for 45 s and a final step at 68 ◦C for 5 min. PCR products were electrophoresed on a 1.0% agarose gel. The DNA of a Spiroplasma species isolated from I. persulcatus in our previous study [23] and sterilized water were included in each PCR run as positive and negative controls, respectively. Primer sets used for each assay are shown in Table1[ 13,36]. The amplified PCR products were purified using ExoSAP-IT Express PCR Cleanup Reagent (Thermo Fisher Scientific, Tokyo, Japan). Sanger sequencing was performed using the BigDye Terminator version 3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA) and the ABI Prism 3130xl Genetic Analyzer according to the manufacturer’ s instructions. Sequence data were assembled using ATGC software version 6.0.4 (GENETYX, Tokyo, Japan).

2.5. Molecular Characterization of Spiroplasma To further characterize Spiroplasma in ticks, additional PCRs based on the 16S–23S rRNA intergenic transcribed spacer (ITS) region (301 bp), chromosomal replication ini- tiator protein dnaA (dnaA) (515 bp), and RNA polymerase B (rpoB) genes (1703 bp) were performed with primers widely used for the characterization of Spiroplasma in arthro- pods [2,36]. These PCRs were performed for selected samples using the following criteria: (1) more than three samples (when available) were selected for each 16S rDNA allele; (2) the samples were selected from each tick species when the 16S rDNA allele was obtained from multiple tick species. The PCRs were carried out as described above, except that 56 and 52 ◦C were used as the annealing temperatures for ITS and dnaA PCRs, respectively. The primer sets used for each assay are shown in Table1. All PCR amplicons were sub- jected to Sanger sequencing analysis. The sequences obtained were submitted to the DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) under specific accession numbers (16S rDNA: LC592079–LC592113; ITS: LC592139–C592161; dnaA: LC592127–LC592138; rpoB: LC592114–LC592126). Microorganisms 2021, 9, 333 4 of 17

Table 1. Primers used in the present study.

Primer Sequence (5’-3’) Target Gene Annealing Temperature (◦C) Purpose Amplicon Size (bp) Reference spi_f1 GGGTGAGTAACACGTATCT 16S rDNA 60 PCR 1028 [13] spi_r3 CCTTCCTCTAGCTTACACTA 16S_s1 ACCTTACCAGAAAGCCACGG 16S rDNA NA Sequencing NA This study 16S_s2 AGACCTTCATCAGTCACGCG 16S rDNA NA Sequencing NA This study 16S_s3 GTAATATGTGCCAGCAGCCG 16S rDNA NA Sequencing NA This study 16S_s4 ACCGCATTCTCCATCAGCTT 16S rDNA NA Sequencing NA This study SP-ITS-JO4 GCCAGAAGTCAGTGTCCTAACCG ITS1 56 PCR 301 [13] SP-ITS-N55 ATTCCAAGCCATCCACCATACG SRdnaAF1 GGAGAYTCTGGAYTAGGAAA dnaA 52 PCR 515 [36] SRdnaAR1 CCYTCTAWYTTTCTRACATCA RpoBF1 ATGGATCAAACAAATCCATTAGCAGA rpoB 60 PCR 1703 [36] RpoBR2 GCATGTAATTTATCATCAACCATGTGTG RpoB_s1 TGACCATTACTACGAGCAATAACA rpoB NA Sequencing NA This study RpoB_s2 CCCCTGTTTTTGATGGTGCA rpoB NA Sequencing NA This study NA, not applicable. Microorganisms 2021, 9, 333 5 of 17

2.6. Phylogenetic Analysis Phylogenetic trees were constructed based on the partial sequences of 16S rDNA, dnaA, rpoB genes, and ITS region. The nucleotide sequences obtained were aligned with repre- sentative sequences of known Spiroplasma species available in GenBank as implemented in MEGA7 [30,37]. The reference sequences of ITS region of S. ixodetis were obtained by de novo assembly of Illumina raw reads of Spiroplasma-infected African monarch butter- fly chrysippus deposited in the sequence read archives (SRA) of the NCBI with accession numbers of SRX3872086 and SRX3872088-SRX3872090 [38] using CLC Genomics Workbench v 20.0.4 (Qiagen, Hilden, Germany). Phylogenetic trees were constructed using maximum likelihood (ML) method with bootstrap tests of 1000 replicates. The sequence data of the evolutionary models were determined using the Akaike information criterion with MEGA7 [37].

2.7. Phylogenetic Analysis Spiroplasma infection in ticks can be affected by various extrinsic and intrinsic factors. Here, the extrinsic factors included sampling district, city/town, season, month, and year variations, and the intrinsic factors were tick species and sex. First, multicollinearity among the explanatory variables was examined using pairwise correlations and the “VIF” function in R package [39] to determine whether multicollinearity was likely to influence LMM results. A correlation between several variables affecting Spiroplasma infection in tsetse flies was reported in a previous study [40]. To identify this possible correlation in ticks, we performed multiple correspondence analysis (MCA) using the “MCA” and “fviz_mca_var” functions in the R packages FactoMineR and Factoextra, respectively [41]. We used an LMM to resolve the correlation among the predictor variables associated with Spiroplasma infection in ticks. We fit the LMM with the predictor variables (sampling season, year, tick sex, and species) as the fixed effects with and without geographic location (district) as the random effect. This was followed by testing in additional LMMs using combinations of the predictor variables with district as the random effect variable and Spiroplasma infection as the response variable. We compared the effectiveness of the tested models with the Chi-square test using the “ANOVA” function in R software. Finally, the “lmer” function in the R package lme4 [42] was used for the selected LMM, with each detected Spiroplasma allele as the response variable.

3. Results 3.1. Infection Rate of Spiroplasma in Different Tick Species In this study, 109 of 712 samples (15%) were positive for Spiroplasma infection. Among the 20 different tick species, eight tick species were positive for Spiroplasma infection, and the highest infection rate was observed in I. ovatus (84%; 67/80), followed by H. kitaokai (35%; 27/78), I. turdus (17%; 1/6), I. persulcatus (16%; 9/55), D. taiwanensis (11%; 1/9), I. pavlovsky (8%; 2/26), A. testudinarium (4%; 1/26), and H. flava (2%; 1/65) (Figure1). Only female ticks were positive for the infection in I. turdus, D. taiwanensis, and H. flava, while only one male was positive in A. testudinarium. The difference in Spiroplasma infection rates between male and female ticks was not statistically significant (Fisher’s exact test). Spiroplasma-positive ticks were detected from most of the geographic blocks except for Kanto and Okinawa (Figure2). Microorganisms 2021, 9, 333 6 of 17 Microorganisms 2021, 9, x FOR PEER REVIEW 6 of 18

Microorganisms 2021, 9, x FOR PEER REVIEW 6 of 18

Figure 1. FigureSpiroplasma 1. Spiroplasma-positive-positive rates rates of of differentdifferent tick tick species. species. Blue and Blue orange and bars orange represent bars male represent and female male ticks, and respec- female ticks, respectively.tively.Figure The The 1. numbers Spiroplasma numbers at-positive the the top top ofrates ofthe theof bars different bars indicate indicate tick the species. number the Blue number of Spiroplasmaand or ofangeSpiroplasma-positive bars represent ticks/number-positive male and ticks/number of femaletested ticks.ticks, respec- of tested ticks. tively. The numbers at the top of the bars indicate the number of Spiroplasma-positive ticks/number of tested ticks.

Figure 2. A map of Japan showing the Spiroplasma-positive rate of each geographical block. The numbers in the parentheses refer to the number of Spiroplasma-positive ticks/number of tested ticks. Figure 2. AFigure map 2. of A Japanmap of showingJapan showing the Spiroplasma the Spiroplasma-positive-positive raterate of of each each geographical geographical block. block. The numbers The numbers in the parentheses in the parentheses refer to the number of Spiroplasma-positive ticks/number of tested ticks. refer to the number of Spiroplasma-positive ticks/number of tested ticks.

3.2. 16S rDNA Genotyping of Spiroplasma in Ticks A total of 101 amplicons of 16S rDNA were successfully sequenced, resulting in 17 different 16S rDNA alleles (G1–G17) (Table2). Eight samples failed in sequencing due to mixed signals. Of the 17 alleles, 13 alleles (G3–G8, and G11–G17) were detected in a single tick species. Two alleles (G1 and G10) were detected in two different tick species: G1 from I. ovatus and I. persulcatus and G10 from A. testudinarium and I. persulcatus. One allele (G2) was detected in three different tick species: I. ovatus, I. persulcatus, and H. kitaokai. Another allele (G9) was observed in four different tick species: I. turdus, I. persulcatus, D. taiwanensis, and H. kitaokai. The detected alleles were classified into the Ixodetis or CCM group in Microorganisms 2021, 9, 333 7 of 17

a phylogenetic tree based on the sequences of 16S rDNA (Figure3). G10 and G17 were clustered with Spiroplasma spp. in the CCM group, whereas other alleles were grouped with members in the Ixodetis group. G10 and G17 showed 99.7% and 99.4% sequence identity, respectively, to S. mirum (CP006720). Alleles in the Ixodetis group formed a cluster with S. ixodetis found in Ixodes, Rhipicephalus, and Dermacentor ticks in other countries and a Microorganisms 2021, 9, x FOR PEER REVIEW 8 of 18 variety of arthropods such as ladybird, , louse, butterfly, planthopper, and mealybug (Figure3).

Mycoplasma mycoides (BX293980)

89 Spiroplasma litorale (AY189306) (horsefly) 84 96 Spiroplasma turonicum (AY189310) (wasp) Spiroplasma corruscae (AY189128) (firefly) Spiroplasma diminutum (AY189130) (mosquito) 87 Spiroplasma diabroticae (M24482) (beetle)

4 Spiroplasma monobiae (M24481) (wasp) 73 Spiroplasma velocicrescens (AY189311) (wasp)

4 Spiroplasma culicicola (AY189129) (mosquito) 99 Spiroplasma apis (M23937) (honeybee) Apis group 28 Spiroplasma montanense (AY189307) (horsefly) 3 Spiroplasma taiwanense (M24476) (mosquito) Spiroplasma clarkii (M24474) (beetle) Spiroplasma gladiatoris (M24475) (horsefly) 0 Spiroplasma leptinotarsae (AY189305) (shrimp)

4 Spiroplasma lampyridicola (AY189134) (beetle) 25 Spiroplasma alleghenense (AY189125) (scorpion fly) 99 Spiroplasma sabaudiense (AY189308) (mosquito) (M24483) (fruitfly)

98 (X63781) () Spiroplasma melliferum (AY325304)(shrimp) 72 Spiroplasma penaei (AY771927) (shrimp) Spiroplasma chrysopicola (AY189127) (shrimp) CCM group 99 99 Spiroplasma syrphidicola (AY189309) (shrimp) Spiroplasma mirum (CP006720) (tick, Haemaphysalis leporispalustris) G17 G10 Spiroplasma sp. (AJ006775) (ladybird) G16 G14 G13 G12 G11

61 G8 G7 100 G6 G5 G4 G3 G1 Spiroplasma ixodetis (KY674401.1) (tick, Ixodes arboricola) Spiroplasma ixodetis (KY674420.1) (tick, Rhipicephalus pusillus) Spiroplasma ixodetis (KY674416.1) (tick, Rhipicephalus annulatus) 72 87 Spiroplasma ixodetis (KY674419.1) (tick, Rhipicephalus geigyi) Spiroplasma ixodetis (MK241976.1) (tick, Rhipicephalus decoloratus) Ixodetis group Spiroplasma sp. (AM087471) (ladybird beetle) Spiroplasma sp. (AB048263) (pea louse) Spiroplasma sp. (AJ132412) (japanese ladybird) Spiroplasma ixodetis (NR104852) (tick, Ixodes pacificus) Spiroplasma ixodetis (KY674403.1) (tick, Ixodes frontalis) Spiroplasma ixodetis (KY674415.1) (tick, Dermacentor marginatus) Spiroplasma ixodetis (KY674411.1) (tick, Ixodes uriae) 61 Spiroplasma ixodetis (KY674410.1) (tick, Ixodes ricinus) Spiroplasma ixodetis (KY674405.1) (tick, Ixodes pacificus) Spiroplasma ixodetis (KY674404.1) (tick, Ixodes kerguelenensis) G2 G9 G15 Spiroplasma ixodetis (KP967685) (tick, Ixodes ricinus) Spiroplasma sp. (AJ245996) () Spiroplasma sp. (AB553862) (planthopper) Spiroplasma sp. (AB030022) (mealybug)

0.020 Figure 3.FigureA phylogenetic3. A phylogenetic tree tree basedbased on on the the sequences sequences of 16S of rD 16SNA. The rDNA. analysis The was analysis performed was using performed a maximum-likeli- using a maximum- hood method based on the Hasegawa–Kishino–Yano model with bootstrap tests of 1000 replicates in MEGA7. A discrete likelihoodGamma method distribution based on was the used Hasegawa–Kishino–Yano to model evolutionary rate model differences with bootstrapamong sites tests (five of categories 1000 replicates (+G, parameter in MEGA7. = A discrete Gamma0.2496)). distribution The sequences was used obtained to model in this evolutionary study are included ratedifferences with allele name amongs provided sites (fivein Table categories 2 and are (+G, shownparameter in red. = 0.2496)). The sequencesThe sequences obtained of other in Spiroplasma this study species are were included retrieved with from allele GenBank. names The providedhost is indicated in Table in the2 parenthesisand are shown for each in red. The Spiroplasma sequence. sequences of other Spiroplasma species were retrieved from GenBank. The host is indicated in the parenthesis for each Spiroplasma sequence.

Microorganisms 2021, 9, 333 8 of 17

Table 2. Spiroplasma 16S rDNA alleles and their geographic origins and host tick species.

No. of Positive/No. of Tested (%) 16S rDNA Allele Tick Species Hokkaido Tohoku Kanto Chubu Kinki Chugoku Sikoku Kyushu Okinawa G1 I. ovatus 21/44 (48) 2/32 (6) - 0/4 (0) - - - - - G1 I. persulcatus 1/39 (3) 0/8 (0) - 0/4 (0) 0/4 (0) - - - - G2 H. kitaokai - 0/5 (0) - - 2/12 (17) - 0/36 (0) 0/45 (0) - G2 I. ovatus 1/44 (2) 0/32 (0) - 0/4 (0) - - - - - G2 I. persulcatus 3/39 (7) 0/8 (0) - 0/4 (0) 0/4 (0) - - - - G3 I. ovatus 3/44 (7) 1/32 (3) - 3/4 (75) - - - - - G4 I. ovatus 1/44 (2) 0/32 (0) - 0/4 (0) - - - - - G5 I. ovatus 1/44 (2) 0/32 (0) - 0/4 (0) - - - - - G6 I. ovatus 3/44 (7) 1/32 (3) - 1/4 (25) - - - - - G7 I. ovatus 1/44 (2) 1/32 (3) - 0/4 (0) - - - - - G8 I. ovatus 1/44 (2) 0/32 (0) - 0/4 (0) - - - - - G9 D. taiwanensis - 0/1 (0) - - 1/4 (25) - - 0/4 (0) - G9 H. kitaokai - 0/5 (0) - - 3/12 (25) - 2/36 (6) 18/45 (40) - G9 I. persulcatus 0/39 (0) 0/8 (0) - 0/4 (0) 4/4 (100) - - - - G9 I. turdus - - - - 0/2 (0) - 0/2 (0) 1/2 (50) - G10 A. testudinarium - - - - - 1/9 (11) 0/15 (0) 0/2 (0) - G10 I. persulcatus 0/39 (0) 1/8 (13) - 0/4 (0) 0/4 (0) - - - - G11 I. ovatus 0/44 (0) 16/32 (50) - 0/4 (0) - - - - - G12 I. ovatus 0/44 (0) 2/32 (6) - 0/4 (0) - - - - - G13 I. pavlovsky 1/26 (4) ------G14 H. kitaokai - 0/5 (0) - - 0/12 (0) - 0/36 (0) 1/45 (2) - G15 H. kitaokai - 1/5 (20) - - 0/12 (0) - 0/36 (0) 0/45 (0) - G16 I. ovatus 0/44 (0) 1/32 (3) - 0/4 (0) - - - - - G17 I. pavlovsky 1/26 (4) ------Microorganisms 2021, 9, 333 9 of 17

3.3. Characterization of Spiroplasma Based on the Sequences of ITS Region, dnaA, and rpoB Genes To further characterize Spiroplasma in ticks, 50 Spiroplasma-positive samples were selected based on 16S rDNA genotyping results. The ITS region was amplified in all 16S rDNA alleles, resulting in five different alleles (T1–T5) (Table3). T1 was the most abun- dant allele detected in the samples of 10 different 16S rDNA alleles (G1, G2, G4, G8–G10, and G12–G15). Phylogenetic analysis revealed that T4 was clustered with Spiroplasma spp. including S. mirum in the CCM group, whereas T1-T3 and T5 formed a cluster with S. ixode- tis reported from butterflies (Figure4). There was a discrepancy between the 16S rDNA and ITS genotyping results; haplotype SP22 had a 16S rDNA allele (G10) belonging to the CCM group and an ITS allele (T1) belonging to the Ixodetis group. PCR amplification of the dnaA and rpoB genes were only successful for six and seven 16S rRNA alleles, respectively. ML trees based on dnaA and rpoB are shown in Supplementary Figures S3 and S4, respectively.

Table 3. Multi-locus sequence typing of Spiroplasma in ticks.

16S Spiroplasma Haplotype ITS dnaA rpoB Tick Species rDNA SP1 G1 T3 A1 B1 I. ovatus SP2 G1 T1 - - I. persulcatus SP3 G2 T1 A1 B4 H. kitaokai SP4 G2 T1 A1 - H. kitaokai SP5 G2 T2 - - I. ovatus SP6 G2 T1 A2 B1 I. persulcatus SP7 G2 T1 A2 B7 I. persulcatus SP8 G2 T1 - - I. persulcatus SP9 G3 T2 - - I. ovatus SP10 G4 T1 A2 B3 I. ovatus SP11 G5 T3 A2 B3 I. ovatus SP12 G6 T2 - - I. ovatus SP13 G7 T2 A1 - I. ovatus SP14 G8 T1 A2 B3 I. ovatus SP15 G9 T1 A2 B2 D. taiwanensis SP16 G9 T1 A2 B4 H. kitaokai SP17 G9 T1 A2 B7 H. kitaokai SP18 G9 - A2 B7 H. kitaokai SP19 G9 T1 - - I. persulcatus SP20 G9 T1 A1 - I. persulcatus SP21 G9 T1 A1 B7 I. persulcatus SP22 G9 T5 - B6 I. persulcatus SP23 G9 T1 - B5 I. turdus SP24 G10 T1 - - A. testudinarium G10 T1 - - I. persulcatus SP25 G11 T2 - - I. ovatus SP26 G12 T1 - - I. ovatus SP27 G13 T1 - - I. pavlovsky SP28 G14 T1 - - H. kitaokai SP29 G15 T1 - - H. kitaokai SP30 G16 T2 - - I. ovatus SP31 G17 T4 - - I. pavlovsky -, Not amplified. Microorganisms 2021, 9, x FOR PEER REVIEW 10 of 18 Microorganisms 2021, 9, 333 10 of 17

Mycoplasma mycoides (BX293980)

95 Spiroplasma alleghenense (CP031376) (scorpion fly) 99 Spiroplasma sabaudiense (CP006934) (mosquito)

73 Spiroplasma monobiae (CP025543) (honeybee) Spiroplasma cantharicola (CP012622) (soldier beetle) 38 47 Spiroplasma apis (CP006682) (honeybee) Spiroplasma floricola (CP025057) (american tulip tree) Spiroplasma taiwanense (CP005074) (mosquito) Apis group 63 Spiroplasma culicicola (CP006681) (mosquito)

32 Spiroplasma helicoides (CP017015) (horsefly) 10 Spiroplasma clarkii (CP024870) (green june beetle)

7 Spiroplasma turonicum (CP013860) (horsefly)

48 Spiroplasma litorale (CP012357) (horsefly) 90 Spiroplasma corruscae (CP022535) (firefly)

99 Spiroplasma citri (CP013197) (orange) Spiroplasma phoeniceum (CP031088) (rosy periwinkle) Spiroplasma chrysopicola (CP005077) (fly) Spiroplasma syrphidicola (CP005078) (fly) CCM group

98 Spiroplasma mirum (CP002082) (tick, Haemaphysalis leporipalustris) 94 41 Spiroplasma atrichopogonis (CP011855) (biting midges) T4 Spiroplasma ixodetis (SRR6925898) (butterfly) 42 Spiroplasma ixodetis (SRR6925896) (butterfly) Spiroplasma ixodetis (SRR6925895) (butterfly) 100 Spiroplasma ixodetis (SRR69525894) (butterfly) Ixodetis group T1 T5 49

65 T3 89 T2

0.050

FigureFigure 4. AA phylogenetic phylogenetic tree tree based based on on the the sequences sequences of ITS of ITS regi region.on. The Theanalysis analysis was wasperformed performed using using a maximum-likeli- a maximum- likelihoodhood method method based based on the on theTamura Tamura 3-parameter 3-parameter model. model. A Adisc discreterete Gamma Gamma distribution distribution was was used used to to model model evolutionary raterate differencesdifferences among among sites sites (five (five categories categories (+G, (+G, parameter paramete =r 0.2599))= 0.2599)) with with bootstrap bootstrap tests tests of 1000 of 1000 replicates replicates in MEGA7. in MEGA7. The sequencesThe sequences obtained obtained in this in study this study are included are included with allele with names allele providednames provided in Table 3in and Table are 3 shown and are in red.shown The in sequences red. The ofse- otherquencesSpiroplasma of other Spiroplasmaspecies were species retrieved were from retrieved GenBank. from GenBank.

3.4. Effect of the Genetic Background on Spiroplasma Infection Based on on the the estimation estimation of of multicollinearit multicollinearityy using using VIF, VIF, the thenumber number of degrees of degrees of free- of freedomdom (Df) (Df)was wasmore more than than1 for 1all for variables all variables except except the year; the thus, year; we thus, calculated we calculated the gener- the generalizedalized variance variance inflation inflation factors factors (GVIFs). (GVIFs). The Df The is Df equal is equal to the to number the number of associated of associated co- 1/2Df coefficientsefficients for for a aGVIF. GVIF. Therefore, Therefore, we we used GVIF1∕2Df toto make make GVIF valuesvalues comparablecomparable among those those with with different different numbers numbers of of Df. Df. High High collinearity collinearity is usually is usually indicated indicated by VIF by VIF> 20. > However, 20. However, multicollinearity multicollinearity analysis analysis using usingVIF indicated VIF indicated low multicollinearity low multicollinear- with ityall variables with all variables(VIF < 5), (suggestingVIF < 5), suggesting that linear that regression linear regressionmodels would models not wouldbe influenced not be influencedby a combination by a combination of these variables. of these Multicollinearity variables. Multicollinearity analysis showed analysis that showed there was that a theremoderate was correlation a moderate between correlation the betweenpredictor the variables predictor (season variables and (seasonmonth; anddistrict month; and

Microorganisms 2021, 9, 333 11 of 17

district and city/town) (Table S1). Both month and city/town variables were excluded from further analysis. Then, MCA was performed to identify associations between the predictor variables. The strongest association was detected between district, species, and season (Figure S1). LMM analysis using the predictor variables (season, year, sex, and species) revealed that the introduction of district as the random effect variable improved the models significantly (p 5 0.001) (Table4). Moreover, when tick species was used as the principal predictor, the model for testing Spiroplasma infection in ticks was improved − (p 5 1.73 × 10 75; Table5).

Table 4. LMM to test the correlation between each predictor with Spiroplasma infection using district as the random effect variable.

Predictor Random Model AIC BIC logLik Dev Chisq Df Pr (>Chisq) Variable Variable M1-1 Species No 99.33 195.26 −28.67 57.33 NA NA NA M1-2 Species District 74.43 174.93 −15.22 30.43 26.90 1 2.14 × 10−7 *** M2-1 Year No 467.30 481.00 −230.65 461.30 NA NA NA M2-2 Year District 459.39 477.67 −225.70 451.39 9.90 1 0.00164998 *** M3-1 Sex No 495.23 513.50 −243.61 487.23 NA NA NA M3-2 Sex District 451.24 474.08 −220.62 441.24 45.99 1 1.19 × 10−11 *** M4-1 Season No 538.56 556.83 −265.28 530.56 NA NA NA M4-2 Season District 465.98 488.82 −227.99 455.98 74.58 1 5.83 × 10−18 *** NA: Not applicable; AIC: Akaike information criterion; BIC: Bayesian information criterion; logLik: log-likelihood; ChiSq: ANOVA Chi-square value; Dev: Deviance of the model; Df: Chi-square degrees of freedom; Pr(>Chisq): ANOVA p value. The level of significance was marked as *** if p < 0.0001 and not marked if p > 0.05.

Table 5. Effect of several variables on the probability of Spiroplasma infection in the LMM.

Random Model Predictor Variable AIC BIC LogLik Deviance Chisq Df Pr (>Chisq) Variable M5 NO District 464.22 477.92 −229.11 458.22 NA NA NA M7 Year District 459.39 477.67 −225.70 451.39 6.82 1 0.00899482 ** M8 Season District 451.24 474.08 −220.62 441.24 10.16 1 0.00143586 ** M9 Sex District 465.98 488.82 −227.99 455.98 0.00 0 NA M6 Species District 74.43 174.93 −15.22 30.43 425.55 17 8.34 × 10−80 *** M10 Season + Species District 71.83 181.47 −11.92 23.83 6.60 2 0.03694614 * M11 Species + Season District 71.83 181.47 −11.92 23.83 0.00 0 NA Species + Season + M12 District 69.87 188.64 −8.93 17.87 5.97 2 0.05065574 . Sex NA: Not applicable; AIC: Akaike information criterion; BIC: Bayesian information criterion; logLik: log-likelihood; ChiSq: ANOVA Chi-square value; Dev: Deviance of the model; Df: Chi-square degrees of freedom; Pr(>Chisq): ANOVA p value. The level of significance was marked as *** if p < 0.0001 and not marked if p > 0.05.

The association between Spiroplasma 16S rDNA alleles and host tick species was estimated separately using the best-fit LMM. This analysis was applicable to six alleles (G1–G3, G6, G9, and G11). However, the analysis was not appropriate for the other 11 alleles due to the small sample size (less than five). The analysis revealed that the probability of infection with G1 and G11 was significantly associated with I. ovatus; however, compared with other tick species, H. kitaokai had a significantly higher probability of infection with G9 (Table6 and Table S2–S4). Microorganisms 2021, 9, 333 12 of 17

Table 6. Association between Spiroplasma 16S rDNA alleles and tick species.

16S rDNA Allele Tick Species (No. of Positive Samples) Significance G1 I. ovatus (n = 23), I. persulcatus (n = 1) I. ovatus H. kitaokai (n = 2), I. ovatus (n = 1), I. G2 Not significant persulcatus (n = 3) G3 I. ovatus (n = 7) Not significant G4 I. ovatus (n = 1) NA G5 I. ovatus (n = 1) NA G6 I. ovatus (n = 5) Not significant G7 I. ovatus (n = 2) NA G8 I. ovatus (n = 1) NA D. taiwanensis (n = 1), H. kitaokai (n = 23), I. G9 H. kitaokai turdus (n = 1), I. persulcatus (n = 4) G10 A. testudinarium (n = 1), I. persulcatus (n = 1) NA G11 I. ovatus (n = 16) I. ovatus G12 I. ovatus (n = 2) NA G13 I. pavlovsky (n = 1) NA G14 H. kitaokai (n = 1) NA G15 H. kitaokai (n = 1) NA G16 I. ovatus (n = 1) NA G17 I. pavlovsky (n = 1) NA NA: not applicable.

4. Discussion Prior to this study, there was only limited information available on the prevalence and genetic diversity of tick-associated Spiroplasma in Japan. In addition to three tick species (H. kitaokai, I. ovatus, and I. persulcatus) that were previously revealed to harbour Spiroplasma [24,32], five additional species, i.e., A. testudinarium, D. taiwanensis, H. flava, I. pavlovsky, and I. turdus, were found to be infected with Spiroplasma, thus expanding our knowledge of the host range of tick-associated Spiroplasma in Japan. The infection rate of Spiroplasma ranged from 0% to 84% depending on the tick species. To investigate whether this difference in infection rate is determined by the tick species or other factors, LMM analysis was performed. The results indicated that Spiroplasma infection was mainly influenced by the species of ticks but less likely to be influenced by temporal and seasonal factors (Table5). Although the prevalence of Spiroplasma in tick populations has not been well understood, several previous studies reported that the Spiroplasma infection rates are variable between populations such as in I. arboricola, I. ricinus, and R. decoloratus [28,43]. A study investigating Spiroplasma infection rates in natural populations in the southwestern United States and northwestern Mexico observed varying infection rates depending on the fly species [44]. In the same study, there was a difference in Spiroplasma infection rates in two fly species between the two collection sites. Similarly, in our LMM analysis, the introduction of district as the random effect variable improved the models significantly (Table4), indicating that the Spiroplasma infection status in ticks may be partially influenced by the sampling location. The highest infection rate was observed in I. ovatus; 82% (32/39) of males and 85% (35/41) of females were positive based on PCR amplification of Spiroplasma 16S rDNA (Figure1). Sequencing analysis of PCR amplicons identified 11 Spiroplasma alleles in this tick species (Table3). Furthermore, H. kitaokai, the second most infected species (28% (11/40) of males and 42% (16/38) of females), had four different Spiroplasma alleles. The associa- tion between specific 16S rDNA alleles (G1, G9, and G11) and their host tick species was statistically confirmed (Table6). The presence of these alleles resulted in the high overall infection rates in I. ovatus and H. kitaokai. These Spiroplasma alleles may have adapted to the tick environment, which is important for symbionts [45]. The transmission of symbionts occurs mainly through the vertical or horizontal route. Vertical transmission involves the dispersal of symbionts and occurs primarily from the mother to offspring. Horizontal transmission occurs via host-to-host contact and acquisition from the environment [45]. The Microorganisms 2021, 9, 333 13 of 17

high infection rates observed in I. ovatus and H. kitaokai suggest the vertical transmission of Spiroplasma in these tick species. Symbionts can positively affect the nutrition, repro- duction, and defence of their hosts. These positive effects may promote the coexistence or coevolution of symbionts and their hosts [45]. Therefore, it is of particular interest to investigate whether Spiroplasma affects tick fitness, as it may help understand the close association between Spiroplasma and ticks. Among the three Spiroplasma clades, tick-associated Spiroplasma has only been identi- fied in the Ixodetis and CCM groups. In the present study, most of the samples were classi- fied as belonging to the Ixodetis group (n = 98), and only three samples were classified as be- longing to the CCM group (Figure3). Considering that most of the Spiroplasma species from ticks identified in previous studies belong to the Ixodetis group [21,22,24,25,29,30,43,46], this group of Spiroplasma may be widely distributed in the world. On the other hand, there is a lack of information on the geographic distribution and host range of tick-associated Spiroplasma in the CCM group. The alleles G10 and G17 obtained in the present study showed high sequence identities (99.7% and 99.4%, respectively) to S. mirum, which has been found to cause persistent infection in the mouse brain [47] and neurological dete- rioration and spongiform encephalopathy in suckling rats [48,49]. Furthermore, several ruminants such as deer, sheep, and goats developed spongiform encephalopathy in a dose-dependent manner when experimentally inoculated with S. mirum in their brains [50]. The alleles G10 and G17 were obtained from A. testudinarium, I. pavlovsky, and I. persulcatus, whose primary hosts include domestic and wild ruminants such as cattle and sika deer in Japan [51,52]. Furthermore, A. testudinarium and I. persulcatus are human-biting species that serve as main vectors for human tick-borne diseases [53,54]. Hence, it is important to investigate the potential of these Spiroplasma alleles as agents of human and animal diseases. The 16S rDNA-based genotyping of 101 Spiroplasma-positive samples identified 17 alleles, some of which were observed in more than two different tick species (Table2). However, further characterization by sequencing additional genes (ITS, dnaA, and rpoB) divided them into 31 haplotypes, and only one of them (SP24) was observed in two tick species (A. testudinarium and I. persulcatus) (Table3). A previous study suggested the possi- ble horizontal transmission of Spiroplasma between different ticks and other arthropods, considering that tick-derived S. ixodetis did not form a tick species-specific [30]. Our results indicated that horizontal transmission among tick species is not common, at least among the tested tick species. However, the fact that certain alleles (G2, G9, and G15) in the Ixodetis group were more related to Spiroplasma found in other arthropods than other alleles found in ticks highlights the important role of horizontal transmission between arthropods in the spread of Spiroplasma in ticks, as suggested previously [30]. The genes dnaA and rpoB are frequently used in the detection and characterization of Spiroplasma alleles in various arthropods [1,29,36,40,46,55]. In this study, dnaA and rpoB were not amplified in nearly half of the haplotypes tested (Table3). This may be attributed to nucleotide mismatches in the primer annealing sites. To understand the genetic diversity of Spiroplasma and clarify the mode of horizontal transmission in ticks, further assays using different gene targets and primer sets are necessary. A previous study developed a multi-locus sequence typing method based on five genes (16S rDNA, rpoB, dnaK, gyrA, and EpsG) by referring the daft genome of S. ixodetis Y32 type [30]. Considering high PCR success rates reported for ticks and other arthropods, the method might be useful to genotype Spiroplasma in ticks. Some species of Spiroplasma are known to affect host reproductive systems through mechanisms such as male killing [7–10]. For instance, Spiroplasma kills Drosophila males by inducing male X chromosome-specific DNA damage and activating p53-dependent abnormal apoptosis in male embryos [56]. In this study, 49 male ticks and 60 female ticks were infected with Spiroplasma, and there was no statistically significant difference for any of the tested tick species (Figure1). This result is consistent with that of LLM analysis, where sex was not selected as a variable to improve the model of Spiroplasma infection in ticks (Table4). Similarly, two previous studies targeting wild populations of R. decoloratus Microorganisms 2021, 9, 333 14 of 17

and wild and laboratory populations of I. arboricola did not find any association between sex and Spiroplasma infection [27,30]. In a previous study, Spiroplasma was highly abundant in the salivary glands of I. ovatus [23]. It is known that S. citri, a plant pathogenic Spiroplasma, propagates in the salivary glands of hosts such as and is released along with the saliva into a new plant during feeding, which leads to transmission from an infected plant to new arthropod hosts [57,58]. Similarly, the presence of Spiroplasma in the tick salivary glands may cause horizontal transmission via feeding to unidentified hosts. One recent study reported that the salivary protein components of /Spiroplasma-infected spider mites differed from those of uninfected mites [59]. Tick saliva is an important biological material for various processes such as combating host defences, accelerating blood-feeding processes, and facilitating the transmission of pathogens to hosts [60]. Therefore, the effects of Spiroplasma on tick physiology and pathogen transmission involving the tick salivary glands should be clarified in future experimental studies.

5. Conclusions Spiroplasma is one of the most common symbionts in arthropods; however, only limited data are available on species that infect ticks. This study expanded our knowledge of the host range of tick-associated Spiroplasma in Japan. Modelling analysis using tick samples with different infection rates indicated that the host tick species was the primary factor associated with Spiroplasma infection. Moreover, the presence of certain alleles that are highly adapted to specific tick species may explain the high infection rates in I. ovatus and H. kitaokai. A comparison of the alleles suggests that the horizontal transmission of Spiroplasma between tick species may not be a frequent event. Further studies are required to understand the transmission cycle of Spiroplasma species in wild tick populations and their roles in ticks.

Supplementary Materials: The following are available online at https://www.mdpi.com/2076-2 607/9/2/333/s1: Table S1: Multicollinearity analysis of predictive variables, Table S2: A summary for the Linear mixed models (LMM) testing the probability of infection of Spiroplasma allele G1, Table S3: A summary for the Linear mixed models (LMM) testing the probability of infection of Spiroplasma allele G9, Table S4: A summary for the Linear mixed models (LMM) testing the probability of infection of Spiroplasma allele G11, Figure S1: The results of multiple correspondence analysis, Figure S2: Multicollinearity analysis of predictive variables, Figure S3: A phylogenetic tree based on the sequences of rpoB gene, Figure S4: A phylogenetic tree based on the sequences of dnaA gene. Author Contributions: Conceptualization: S.O. and R.N.; methodology: S.O.; formal analysis: S.O., W.M.A.M., and M.A.M.M.; investigation: S.O., K.K. (Kodai Kusakisako), M.J.T., K.M., K.K. (Ken Katakura), N.N., and Y.Q.; writing—original draft preparation: S.O.; writing—review and editing: S.O. and R.N.; supervision: R.N.; funding acquisition: R.N. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by KAKENHI, grant numbers 16H06429, 16K21723, 16H06431, 19H03118, 19F19097, 20K21358, and 20KK0151. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study are available in the DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) and the accession numbers are available in the text. Acknowledgments: We would like to thank to all collaborators who supported in collection of ticks in each prefecture. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Microorganisms 2021, 9, 333 15 of 17

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